LEARNING PATH

Data Scientist

What is a Data Scientist?

Data scientists straddle both the business and technical worlds with deep data analysis to achieve specific outcomes. In the field of machine learning (ML), data scientists design and build models from data, create and work on algorithms, and train models to predict and achieve business goals.

What Will I Learn?

Traditional ML development is a complex, expensive, iterative process made even harder because there are no integrated tools for the entire ML workflow to build, train, and deploy models at scale. This pathway will teach you to complete the entire ML workflow quickly using Amazon SageMaker, and help bring your models from concept to production with high accuracy and low costs.

Build ML models

Amazon SageMaker makes it easy to build ML models at scale and get them ready for training, by providing everything you need to label training data, access and share notebooks, and use built-in algorithms and frameworks.

Train ML models

Amazon SageMaker helps you train ML models by providing you with everything you need to train, tune, and debug models to achieve maximum accuracy.

Deploy ML models

Amazon SageMaker helps you deploy ML models in production on a fully managed infrastructure with constant monitoring to maintain high quality.

Get Started!

This interactive tutorial will help you to build, train, and deploy a ML model in about 10 minutes using Amazon SageMaker.
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Hands-on Tutorials
Explore more tutorials from integrating intelligence to your apps to optimizing your models.
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